This proposal describes a five-year program designed in the short-term to provide additional specific training and mentored research experience to Dr. Shehnaz K. Hussain to enable her to achieve her long-term goal of successfully launching a career as an independent academic researcher and scientist in cancer molecular epidemiology with a focus on infection-related cancers. Dr. Hussain received a Sc.M. in epidemiology from Johns Hopkins, a Ph.D. in epidemiology from U. W. Seattle, was a postdoc at the Karolinska Institute, and is currently a newly appointed Assistant Professor in the UCLA Department of Epidemiology. Dr. Hussain will meet her academic career goals with the help of a highly experienced and supportive interdisciplinary team of mentors including Drs. Zhang (cancer molecular epidemiology), Martinez-Maza (cancer immunology), Detels (HIV/AIDS epidemiology), and Sinsheimer (statistical genetics); a clear and directed career development plan including grant and manuscript writing, didactic training in computational biology, bioinformatics, complex data analysis, and issues in the design/conduct of genome wide association studies, and wet-lab training; a strong and collaborative institutional environment consisting of multiple centers, departments, and schools of UCLA; and a well-defined research project with a high possibility of being developed into an independent research program. The main hypothesis of Dr. Hussain's research project is that adverse genotypes of B cell activation-related genes will be associated with increased risk of HIV-associated non-Hodgkin's lymphoma (AIDS-NHL). Dr. Hussain will conduct a nested case-control study in two well-described HIV cohorts, the MACS and WIHS. TagSNPs in candidate genes, prioritized by putative functionality, will be genotyped in AIDS-NHL cases and matched controls. Multivariate logistic regression models and pathway-based statistical methods will be utilized to determine the association between tagSNPs and haplotypes and AIDS-NHL risk, and to examine whether these associations are modified by other genetic, molecular, or epidemiological factors. This project will integrate high-throughput technologies, innovative statistical methods, and a wealth of previously collected data to extend our understanding of NHL etiology.